Read-Write Graph Visualization for Real-Time Supply Chain Edits
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Graph data networks, particularly in supply chain management, are complex and dynamic, making it difficult for users to comprehend and adapt to rapid changes, as raw data is often incomprehensible and requires millions of calculations for real-time decision-making.
Innovation Solution
A read-write network visualization system that allows users to visually represent and edit graph networks in real-time, enabling immediate updates and simulations of changes, with a user interface that supports editing and calculating new formulas and values based on user interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If graph networks contain thousands or millions of nodes and edges with millions of data elements, then the network can represent complex supply chain relationships, but the raw data becomes incomprehensible to users
Solution Approach 1:
The patent segments the vast graph network data into manageable visual components by displaying only a subset of nodes and edges in the visual representation. The system divides the complex network into manageable portions that can be comprehended visually, allowing users to understand relationships without being overwhelmed by the full scale of millions of data elements.
Solution Approach 2:
The patent introduces a visual representation layer as an intermediary between the raw graph data and the user. This intermediary visual interface transforms incomprehensible raw data into understandable graphical displays, mediating the interaction between users and the complex underlying data structure.
2Adaptability or versatility
If graph networks are dynamic and continually evolve, then the network can adapt to changing supply chain conditions, but it becomes difficult for users to understand and adapt to rapid changes
Solution Approach 1:
The patent implements dynamic visual representations that update in real-time as the graph network evolves. The visual display dynamically adjusts to reflect changes in the underlying data, allowing users to see evolution of the network over time without having to manually update or reconfigure anything. This maintains adaptability while preserving ease of understanding through continuous visual feedback.
Solution Approach 2:
The system provides visual feedback that helps users understand changes in the dynamic network. By visually representing the state of the graph network and updating this representation as data changes, the system gives users feedback about the current state and evolution of the network, making it easier to understand and adapt to rapid changes.
3Productivity
If millions of calculations are required for real-time decision-making in graph networks, then accurate supply chain analysis can be performed, but the complexity of the system increases
Solution Approach 1:
The patent extracts the computational complexity from the user interface layer and places it in the backend processing system. The visual representation layer displays results of calculations without requiring users to understand or manage the complex computational processes. This separates the complexity of millions of calculations from the simplicity of the user interaction layer.
Data Source
AI summary
Systems and techniques for read-write network visualization are described herein. A selected sub-region of a visual representation of a graph network may be displayed based on inputs received from a user. Boundaries for the selected sub-region of the visual representation of the graph network may be calculated. State data may be captured for a portion of the graph network associated with the selected sub-region using the calculated boundaries for the selected sub-region of the visual representation upon activation of an edit mode user interface control. A change to an element of the graph network may be identified. The graph network may be modified based on the change. A formula may be identified that is associated with the element of the graph network. The formula may be automatically recompiled and values for the element of the graph network, and nodes and edges that share a path with the element, may be automatically recalculated using the recompiled formula.